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BBA 123 by Supichi

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BBA 123 is an open-source language model by Supichi. Features: 32b LLM, VRAM: 34.5GB, Context: 32K, Instruction-Based, Code Generating, Merged, LLM Explorer Score: 0.19.

  Merged Model Base model:maldv/awqward2.5-32... Base model:qwen/qwen2.5-coder-...   Codegen   Conversational   Endpoints compatible   Instruct   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Supichi/BBA-123 

BBA 123 Benchmarks

MMLU Pro: 1.85
GPQA: 1.34
MUSR: 2.57
BBH: 2.22
IFEval: 20.8 vs 88 (so35)-76.4%
LLME Score: 0.19424
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
BBA 123 (Supichi/BBA-123)
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BBA 123 Parameters and Internals

LLM NameBBA 123
Repository 🤗https://huggingface.co/Supichi/BBA-123 
Base Model(s)  Qwen/Qwen2.5-Coder-32B-Instruct   maldv/Awqward2.5-32B-Instruct   Qwen/Qwen2.5-Coder-32B-Instruct   maldv/Awqward2.5-32B-Instruct
Merged ModelYes
Model Size32b
Required VRAM34.5 GB
Updated2026-03-30
MaintainerSupichi
Model Typeqwen2
Instruction-BasedYes
Model Files  5.0 GB: 1-of-7   5.0 GB: 2-of-7   4.9 GB: 3-of-7   4.9 GB: 4-of-7   4.9 GB: 5-of-7   4.9 GB: 6-of-7   4.9 GB: 7-of-7
Generates CodeYes
Model ArchitectureQwen2ForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.48.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to BBA 123

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Context / RAM
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...y Qwen2.5coder 32B V24.1q 200K195K / 65.8 GB82
Qwen2.5 32B YOYO MIX128K / 65.7 GB52
Qwen2.5 Coder 32B YOYO128K / 65.8 GB82
QwQ Qwen2.5 Coder Instruct 32B128K / 65.8 GB430
QwQenSeek Coder128K / 65.7 GB145
Rombos Coder V2.5 Qwen 32B128K / 65.8 GB1819
Tessa T1 32B117K / 65.8 GB1022
UIGEN T1.5 32B117K / 65.8 GB1713
Qwen2.5 Coder 32B Instruct32K / 65.8 GB1309221934
Qwen2.5 Coder 32B Instruct32K / 65.8 GB22087
Note: green Score (e.g. "73.2") means that the model is better than Supichi/BBA-123.

Rank the BBA 123 Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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